Scorched by the heat in Arizona

Reader Jeffrey S. saw this graphic inside a Dec 2 tweet from the National Weather Service (NWS) in Phoenix, Arizona.

In a Trifecta checkup (link), I'd classify this as Type QV.

The problems with the visual design are numerous and legendary. The column chart where the heights of the columns are not proportional to the data. The unnecessary 3D effect. The lack of self-sufficiency (link). The distracting gridlines. The confusion of year labels that do not increment from left to right.

The more hidden but more serious issue with this chart is the framing of the question. The main message of the original chart is that the last two years have been the hottest two years in a long time. But it is difficult for readers to know if the differences of less than one degree from the first to the last column are meaningful since we are not shown the variability of the time series.

The green line makes an assertion that 1981 to 2010 represents the "normal". It is unclear why that period is normal and the years from 2011-5 are abnormal. Maybe they are using the word normal in a purely technical way to mean "average." If true, it is better to just say average.

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For this data, I prefer to see the entire time series from 1981 to 2015, which allows readers to judge the variability as well as the trending of the average temperatures. In the following chart, I also label the five years with the highest average temperatures.

Finding meaning in Big Blue California

Via Twitter, Pat complained that this Bloomberg graphic is confusing:

The accompanying article is here. The gist of the report is that electric cars are much more popular on the West coast because the fuel efficiency of such cars goes down dramatically in colder climates. (Well, there are political reasons too, also discussed in the article.)

What makes this chart confusing?

Our eyes are drawn to big blue California, and the big number 25,295. The blue block raises three questions: first, how do we interpret that 25,295 number? How big is it? To what should we compare the number? Second, we notice a blending of labels--California is the only label of a state while all other labels are of regions. Third, the number under West is 31,783, even larger than 25,295 although it gets a smaller font size, a black-and-white treatment, and a seemingly small allocation of space.

It takes a little time to figure out the structure of the graphic. That the baseline is a treemap with the regions, and big blue California is a highlight that sits within the West region.

Tufte would not love the "moivremoire"  patterns, nor do I. I'd have left the background of the entire right side plain white.

I fail to see why this treemap form is preferred to a simple bar chart.

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As I play around with the data, basically playing with stacking the data, I found a way to make a more engaging graphic. This new graphic builds off an insight from this data: that the number of electric cars sold in California is more than all other states combined. So here you go:

Since the article attributes the gap in sales to regional temperature, an even better illustration should bring in temperature data.

 

Enhanced tables, and supercharged spreadsheets with in-cell tech

Old-timer Chris P. sent me to this Bloomberg article about Vanguard ETFs and low-cost funds (link). The article itself is interesting, and I will discuss it on the sister blog some time in the future.

Chris is impressed with this table included with the article:

This table indeed presents the insight clearly. Those fund sectors in which Vanguard does not compete have much higher costs than the fund sectors in which Vanguard is a player. The author calls this the "Vanguard effect."

This is a case where finding a visual design to beat this table is hard.

For a certain type of audience, namely financial, the spreadsheet is like rice or pasta; you simply can't live without it. The Bloomberg spreadsheet does one better: the bands of blue contrast with the white cells, which neatly divides those funds into two groups.

If you use spreadsheets a lot, you should definitely look into in-cell charts. Perhaps Tufte's sparkline is the most famous but use your imagination. I also wish vendors would support in-cell charts more eagerly.

Here is a vision of what in-cell technology can do with the above spreadsheet. (The chart is generated in R.)